title: Comparative analysis of copy number variation detection methods and database construction.
abstract: BACKGROUND
  Array-based detection of copy number variations (CNVs) is widely used for identifying disease-specific genetic variations. However, the accuracy of CNV detection is not sufficient and results differ depending on the detection programs used and their parameters. In this study, we evaluated five widely used CNV detection programs, Birdsuite (mainly consisting of the Birdseye and Canary modules), Birdseye (part of Birdsuite), PennCNV, CGHseg, and DNAcopy from the viewpoint of performance on the Affymetrix platform using HapMap data and other experimental data. Furthermore, we identified CNVs of 180 healthy Japanese individuals using parameters that showed the best performance in the HapMap data and investigated their characteristics.
  
  
  RESULTS
  The results indicate that Hidden Markov model-based programs PennCNV and Birdseye (part of Birdsuite), or Birdsuite show better detection performance than other programs when the high reproducibility rates of the same individuals and the low Mendelian inconsistencies are considered. Furthermore, when rates of overlap with other experimental results were taken into account, Birdsuite showed the best performance from the view point of sensitivity but was expected to include many false negatives and some false positives. The results of 180 healthy Japanese demonstrate that the ratio containing repeat sequences, not only segmental repeats but also long interspersed nuclear element (LINE) sequences both in the start and end regions of the CNVs, is higher in CNVs that are commonly detected among multiple individuals than that in randomly selected regions, and the conservation score based on primates is lower in these regions than in randomly selected regions. Similar tendencies were observed in HapMap data and other experimental data.
  
  
  CONCLUSIONS
  Our results suggest that not only segmental repeats but also interspersed repeats, especially LINE sequences, are deeply involved in CNVs, particularly in common CNV formations.The detected CNVs are stored in the CNV repository database newly constructed by the "Japanese integrated database project" for sharing data among researchers. http://gwas.lifesciencedb.jp/cgi-bin/cnvdb/cnv_top.cgi.
authors.affiliation: Central Research Laboratory, Hitachi Ltd., Tokyo, Japan. asako.koike.ea@hitachi.com
authors.forename: Asako
authors.initials: A
authors.lastname: Koike
authors.forename: Nao
authors.initials: N
authors.lastname: Nishida
authors.forename: Daiki
authors.initials: D
authors.lastname: Yamashita
authors.forename: Katsushi
authors.initials: K
authors.lastname: Tokunaga
mesh_terms: D000465:Algorithms; D044466:Asian People / Q000235:genetics; D056915:DNA Copy Number Variations; D030541:Databases, Genetic; D006801:Humans; D008390:Markov Chains; D008957:Models, Genetic; D020411:Oligonucleotide Array Sequence Analysis